Deciphering distinct pathogenic mechanisms of ankylosing spondylitis and systemic sclerosis via shared biomarkers ZSWIM6 and CCL3L3: Insights from an integrative bioinformatics approach.

Abstract

Ankylosing Spondylitis (AS) and Systemic Sclerosis (SSc) are both autoimmune diseases, albeit with distinct anatomical targets. AS primarily affects the spine and sacroiliac joints, triggering inflammation and eventual fusion of the vertebrae. SSc predominantly impacts the skin and connective tissues, leading to skin fibrosis, thickening, and potential damage to vital organs such as the lungs, heart, and kidneys. Despite their differing anatomical manifestations, inflammation serves as a pivotal factor in both conditions. Exploring the causes of the different pathogenesis of inflammation in AS and SSc could provide new insights into their treatment. We selected RNA-seq profiles of peripheral blood mononuclear cells (PBMCs) from the GEO datasets GSE73754 and GSE19617. DEGs were identified using the Limma R package with an adjusted p-value cutoff of < 0.05. Gene Ontology pathway analysis, SVM recursive feature elimination, and Gene Set Enrichment Analysis (GSEA) were conducted to analyze the DEGs. CIBERSORT was applied to estimate immune cell composition and its correlation with hub genes. Single-cell RNA sequencing data from peripheral blood mononuclear cells in the GSE194315 dataset were included to support differential expression analysis and biomarker identification. Additionally, single-cell RNA sequencing data from bone marrow blood samples were utilized to further validate these findings, offering complementary insights into biomarker expression across distinct sample types. A total of 762 DEGs were identified between AS patients and controls, and 441 DEGs between SSc patients and controls. Both conditions showed enrichment in the Natural killer cell mediated cytotoxicity pathway. ZSWIM6 and CCL3L3 were identified as potential biomarkers in AS and SSc, with significant diagnostic capabilities demonstrated by ROC analysis. Correlation analysis revealed associations between these biomarkers and specific immune cell types. The study utilizing ZSWIM6 and CCL3L3 as potential biomarkers provides deep insights into the distinct molecular mechanisms of SSc and AS. These findings lay the foundation for future research on targeted therapies and enhance our understanding of immune cell interactions in these autoimmune diseases.